Key image generation using piecewise linear chaotic maps and MD5 hashing

In some cases, sensitive images may be shared for research, consultation, or collaboration purposes. These images often need to be stored for extended periods, sometimes decades. Sensitive medical images, financial documents, or confidential government data benefit from encryption to prevent unauthorized individuals or hacking attempts from accessing them. By combining the benefits of Piece-Wise Linear Chaotic Maps (PWLCM) features with Message Digest (MD5), this research provides a novel approach for producing safe key images. In the beginning, we emphasize the necessity of safe key images for cryptography and multimedia applications. Highlighting the PWLCM-based and MD5-based techniques that are currently in use and pointing out their security and complexity shortcomings. The fundamental information section introduces the concepts of PWLCM and MD5 hashing, along with their mathematical underpinnings. Our proposed model is then presented, detailing the steps involved in extracting PWLCM features, incorporating randomness through chaotic maps, and generating a robust key image using MD5 hashing. The program was written using the Python Pi programming language. In a 256*256 size image, there will be 256 potential keys for each pixel. For our proposed method using a 512*512 image size, the key space will be 2512*8=24096. The results section showcases the experimental evaluation of our method, demonstrating its effectiveness in terms of key space, and resistance against common attacks. Finally, the conclusion summarizes the contributions of our work and paves the way for future research directions in secure key image generation.